JP2019509548A - Methods and tools for post-mortem analysis of tripped field devices in the process industry using optical character recognition and intelligent character recognition - Google Patents

Abstract

The method includes capturing (208) at least one screen shot of a display screen including an initial screen shot (300). The method includes a step (212) of deleting text from the initial screenshot to generate a base image (500, 700). The method includes identifying (216) the background (region 0) of the initial screenshot as a closed region. The method includes, for each of the at least one screenshot, storing (222) a time to capture the screenshot (970); identifying text, text color, and text location in the screenshot (212, 226), each closed region (region 1-12) in the screenshot different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot (216, 230), storing (222) the region color and region location for each identified closed region, and storing the text color and text location of the identified text (214, 228). ).

Description

  [0001] The present disclosure is generally directed to control systems. More particularly, the present disclosure describes a post-mortem of a tripped field device in the process industry using optical character recognition (OCR) and intelligent character recognition (ICR). Mortem) is directed to methods and tools for analysis.

  [0002] Because process plants, such as power plants, have frequent tripping problems, process units may generate multiple critical alarms, sometimes leading to outages. When tripping occurs, the operator may wish to review previous values of critical process parameters for any processing unit to diagnose the problem. For example, the operator may wish to consider the last 20 minutes of any processing unit activity during which tripping occurred, but the operator would go back to perform postmortem analysis of the tripping problem, There is no way to re-inspect the plant's console station monitored process unit.

  [0003] An operator monitoring a process unit of a critical process on a console station can visually recognize the device that is currently being tripped. Once recognized, the operator is a comprehensive or convenient tool for viewing historical information on process units (the operator was monitoring via the console station), including one of the tripped devices May not be included. There is no convenient tool to allow an operator to configure a critical device of a process unit that will need to be postmortem analyzed when the process unit is shut down.

  [0004] The present disclosure provides an apparatus and method for performing post-mortem analysis of tripped field devices in the process industry using optical character recognition (OCR) and intelligent character recognition (ICR) techniques.

  [0005] In a first example, the method includes capturing at least one screen shot of a display screen that includes an initial screen shot. The method includes removing text from the initial screenshot to generate a base image. The method includes identifying the background of the initial screenshot as a closed region. The method includes, for each of the at least one screenshot, (i) storing time to capture the screenshot; (ii) identifying text, text color, and text location in the screenshot; iii) identifying each closed region in the screenshot different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot; and (iv) each identified Storing the region color and region location for the closed region, and (v) storing the text color and text location of the identified text.

  [0006] In a second example, an apparatus includes a memory and at least one processor coupled to the memory. The at least one processor is configured to capture at least one screen shot of the display screen including the initial screen shot. At least one processor is configured to delete text from the initial screenshot to generate a base image. At least one processor is configured to identify the background of the initial screenshot as a closed region. At least one processor, for each of the at least one screenshot, (i) stores in memory the time to capture the screenshot, and (ii) identifies the text, text color, and text location in the screenshot. (Iii) identifying each closed region in the screenshot that is different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot; (iv) Configured to store in memory a region color and region location for each identified closed region; and (v) store in memory the text color and text location of the identified text. Is done.

  [0007] In a third example, a non-transitory computer readable medium implementing a computer program is provided. The computer program includes computer readable program code that, when executed by the processing circuit, causes the processing circuit to capture at least one screen shot of the display screen including the initial screen shot. The computer program includes computer readable program code that, when executed by the processing circuit, causes the processing circuit to delete the text from the initial screenshot to generate a base image. The computer program includes computer readable program code that, when executed by the processing circuit, causes the processing circuit to identify the background of the initial screenshot as a closed region. When executed by the processing circuit, the computer program causes the processing circuit to store (i) a time to capture the screen shot in memory for each of the at least one screen shot; and (ii) the text in the screen shot. And (iii) each closed region in the screenshot different from the background of the initial screenshot, and a region color and region for each identified closed region in the screenshot Identifying the location; (iv) storing the region color and region location for each identified closed region; and (v) storing the text color and text location of the identified text. Including computer readable program code.

[0008] Other technical features may be readily apparent to one skilled in the art from the following figures, descriptions, and claims.
[0009] For a more complete understanding of the present disclosure and its features, reference is now made to the following description, taken in conjunction with the accompanying drawings.

[0010] FIG. 1 illustrates an exemplary industrial process control and automation system in accordance with the present disclosure. [0011] FIG. 4 illustrates an exemplary process for performing post-mortem analysis of a tripped field device in the process industry using optical character recognition (OCR) and intelligent character recognition (ICR) techniques according to this disclosure. is there. FIG. 3 illustrates an exemplary process for performing post-mortem analysis of a tripped field device in the process industry using optical character recognition (OCR) and intelligent character recognition (ICR) techniques according to this disclosure. [0012] FIG. 4 illustrates an exemplary base screenshot of an operator console display screen that provides a view of a selected critical device of a process unit in accordance with the present disclosure. [0013] FIG. 4 illustrates the base screenshot of FIG. 3 divided into grids in accordance with the present disclosure. [0014] FIG. 4 illustrates a base screenshot without text in accordance with the present disclosure. [0015] FIG. 6 illustrates regions and subregions of the textless base screenshot of FIG. 5 in accordance with the present disclosure. [0016] FIG. 6 illustrates regions and subregions of a color normalized text-less base screenshot with a grid in accordance with the present disclosure. FIG. 6 illustrates regions and subregions of a color normalized textless base screenshot with a grid in accordance with the present disclosure. [0017] FIG. 4 illustrates an example of a reconstructed image for a time interval during which the initial base screenshot of FIG. 3 was captured in accordance with the present disclosure. FIG. 4 illustrates an example of a reconstructed image for a time interval during which the initial base screenshot of FIG. 3 was captured according to this disclosure. [0018] FIG. 5 illustrates a root cause analysis tool user interface (UI) of a display screen in an operator console according to the present disclosure. FIG. 3 illustrates a root cause analysis tool user interface (UI) of a display screen in an operator console according to the present disclosure. [0019] FIG. 4 illustrates a coordinate system applied to the base screenshot of FIG. 3 in accordance with the present disclosure.

  [0020] The various examples used to describe the principles of the present invention in FIGS. 1-10 described below and in this patent document are merely exemplary, and in any form of the present invention. It should not be construed as limiting the scope. Those skilled in the art will appreciate that the principles of the invention may be implemented in any suitable manner and in any type of suitably configured device or system.

  [0021] FIG. 1 illustrates an exemplary industrial process control and automation system 100 according to this disclosure. As shown in FIG. 1, the system 100 includes various components that enable the production or processing of at least one product or other material. For example, the system 100 can be used to allow control over components in one or more industrial plants. Each plant represents one or more processing facilities (or one or more portions thereof). Exemplary processing facilities include manufacturing plants, chemical plants, crude oil refineries, ore processing plants, and paper or pulp manufacturing and processing plants for producing at least one product or other material. In general, each plant may implement one or more industrial processes and may be referred to individually or collectively as a process system. A process system generally represents any system or portion thereof configured to process one or more products or other materials in some manner.

  [0022] In FIG. 1, system 100 includes one or more sensors 102a and one or more actuators 102b. Sensor 102a and actuator 102b represent components in a process system that can perform any of a wide variety of functions. For example, the sensor 102a can measure a wide variety of characteristics in the process system, such as temperature, pressure, or flow rate. The actuator 102b can change various characteristics in the process system. Each of the sensors 102a includes any suitable structure for measuring one or more characteristics in the process system. Each of the actuators 102b includes any suitable structure for affecting or affecting one or more states in the process system. Exemplary actuators 102b include heaters, motors, catalytic crackers, or valves.

  [0023] At least one network 104 is coupled to the sensor 102a and the actuator 102b. Network 104 allows interaction with sensor 102a and actuator 102b. For example, the network 104 can transport measurement data from the sensor 102a and provide a control signal to the actuator 102b. Network 104 may represent any suitable network or combination of networks. As a specific example, the network 104 may be at least one Ethernet network, an electrical signaling network (such as a HART or FOUNDATION FIELDDBUS network), an air control signaling network, or other or additional type (s) (1). Network (s).

  [0024] Various controllers 106 are coupled directly or indirectly to the network 104. Controller 106 may be used in system 100 to perform various functions. For example, a first set of controllers 106 may use measurements from one or more sensors 102a to control the operation of one or more actuators 102b. The second set of controllers 106 may be used to optimize control logic or other operations performed by the first set of controllers. A third set of controllers 106 can be used to perform additional functions.

  [0025] Controllers 106 are often organized hierarchically in the system. For example, different controllers 106 are used to control individual actuators, sets of actuators that form machines, sets of machines that form units, sets of units that form plants, and sets of plants that form enterprises. obtain. A specific example of the hierarchy of controllers 106 is defined as a “Purdue” model of process control. Controllers 106 at different hierarchical levels can communicate through one or more networks 108 and associated switches, firewalls, and other components.

  [0026] Each controller 106 includes any suitable structure for controlling one or more aspects of the industrial process. At least some of the controllers 106 may be, for example, a robust multivariable predictive control (RMPCT) controller, or a model predictive control (MPC) or other advanced predictive control (APC). Multivariable controllers can be represented, such as other types of controllers that implement predictive controls.

  [0027] Operator access to and interaction with the controller 106 and other components of the system 100 may be performed via various operator consoles 110. As explained above, each operator console 110 may be used to provide information to the operator and to receive information from the operator. For example, each operator console 110 can provide the operator with information identifying the current state of the industrial process, including warnings, alarms, or other conditions associated with the industrial process. Each operator console 110 also receives a set point for process variables controlled by the controller 106, or other information that changes or affects how the controller 106 controls the industrial process. Information that affects how an industrial process is controlled, such as by receiving.

  [0028] Multiple operator consoles 110 may be grouped together and used in one or more control rooms 112. Each control room 112 may include any number of operator consoles 110 in any suitable configuration. In some embodiments, multiple control rooms 112 may control an industrial plant, such as when each control room 112 includes an operator console 110 that is used to manage individual parts of the industrial plant. Can be used.

  [0029] Each operator console 110 includes any suitable structure for displaying information to the operator and interacting with the operator. For example, each operator console 110 may include one or more processors, microprocessors, microcontrollers, field programmable gate arrays, application specific integrated circuits, discrete logic devices, or other processing or control devices. A processing device 114 may be included. Each operator console 110 may also include one or more memories 116 that store instructions and data used, generated, or collected by the processing device (s) 114. Each operator console 110 may further include one or more network interfaces 118 that allow communication over at least one wired or wireless network, such as one or more Ethernet interfaces or wireless transceivers.

  [0030] Operators are generally responsible for managing industrial processes and often need to act quickly and efficiently to maintain safe and beneficial operation. To do this, the operator continuously monitors the current state of the industrial process, evaluates whether the current state requires human intervention, performs (if necessary) intervention, Assess the results. An operator console 110 that supports these functions typically includes one or more display screens, one or more keyboards, and a pointing device, such as a mouse or trackball.

  [0031] When the current state of the industrial process includes a field device that is currently tripped, one or more of the display screens in operator console 110 are the device (s) currently being tripped. Give a visual indicator. The operator monitoring the critical process of the industrial process may recognize that the indicator of the currently tripped device (s) is part of the critical process and the current (s) You may want a comprehensive or useful tool to browse past information for that process unit, including the device being tripped. If field devices are frequently tripping due to electromechanical reasons, plant maintenance personnel schedule maintenance activities related to frequently tripping field devices and also maintain device inventory Can benefit from that.

  [0032] To allow control over the process system, the operator console 110 may include a field asset maintenance system (FAMS) application 120. The FAMS application 120 includes any suitable application for generating a graphical display that represents at least a portion of the process being monitored and / or controlled. The FAMS application 120 may include features of a human-machine interface (HMI) application. An HMI application generally represents an application that generates a graphical display for presenting content to an operator. The graphical display visually represents one or more processes (or portions thereof) being monitored and / or controlled by the operator. The HMI application can present any suitable graphical data to the operator, such as a process schematic diagram that schematically shows the process to be controlled. More specifically, the FAMS application 120 not only provides a view of historical information for process units that include the device (s) that are currently being tripped, but also allows process units to When a stop is reached, such as a stop resulting from one or more trippings, it provides a comprehensive or convenient tool to configure the critical device of the process unit for which post-mortem analysis will be required. The FAMS application 120 allows the operator to play the maintenance view screen in the form of a video and field (s) by using optical character recognition (OCR) and intelligent character recognition (ICR) techniques. To find the cause of device tripping. ICR is an advanced OCR technique, so ICR recognizes custom fonts and symbols.

  [0033] According to the present disclosure, the FAMS application 120 is tripped to the one or more computer processors in the process industry using OCR and ICR techniques when executed by the one or more computer processors. To conduct post-mortem analysis of field devices. The FAMS application 120 provides an operator with tools to select available views of various process units running on various operator consoles 110. The FAMS application 120 allows an operator to select a critical device and monitoring frequency for a process unit in order to capture a snapshot of the view at the selected process unit. The FAMS application 120 archives periodic snapshots of the process unit view on the operator console 110 and stores the periodic snapshots in an encrypted and compressed format to conserve disk space. The FAMS application 120 implements an image processing algorithm so that archiving does not consume too much disk space. When tripping occurs, the FAMS application 120 can provide a snapshot as if the snapshot of the process unit depicts a continuously running process. By using the snapshot provided by the FAMS application 120, the operator can monitor the transition of various critical parameters of all critical devices resulting from the tripping and take preventive action. .

  [0034] Although FIG. 1 illustrates an example of an industrial process control and automation system 100, various changes may be made to FIG. For example, industrial control and automation systems have a wide variety of configurations. The system 100 shown in FIG. 1 is intended to illustrate one exemplary operating environment in which post-mortem analysis of tripped field devices in the process industry is performed using OCR and ICR techniques. ing. FIG. 1 does not limit the present disclosure to a particular configuration or operating environment.

  [0035] FIGS. 2A and 2B illustrate an exemplary method 200 for performing post-mortem analysis of a tripped field device in the process industry using OCR and ICR techniques according to this disclosure. For ease of explanation, FIGS. 2A and 2B are described as if the processing device 114 implements the method 200 by executing the FAMS application 120. The embodiment of the method 200 shown in FIGS. 2A and 2B is for illustration only. Other embodiments may be used without departing from the scope of this disclosure.

  [0036] The method 200 includes five stages. Stage 1202 is an initialization stage for preparing a base image. Stage 2 204 is a data capturing stage for capturing screenshots for each interval. Data reconstruction stage 206 includes stage 3 240, stage 4 250, and stage 5 252. Stage 3 240 includes a method of forming an image from stored data. Stage 4 250 includes identifying images and data having specific behavior. Stage 5 252 includes implementing a method for representing stored data in the tool to perform root cause analysis (RCA). These five stages may be associated with a centralized database for storing data, thus making screen data accessible to the operator through the FAMS application 120.

  [0037] Stage 1 202 includes acts 208-220. In operation 208, the processing device 114 captures the base screenshot 300 (shown in FIG. 3). This initial image of the operator console display screen view is captured by the FAMS application 120 and is the base for subsequent images.

  [0038] At operation 210, the processing device 114 divides the initial base screenshot 300 into a grid 400 (shown in FIG. 4). For example, the base screenshot 300 is divided into a set of blocks based on the image size. This is needed to avoid scaling problems. Scaling problems can occur when this algorithm is run on multiple screens of different resolutions for the same process unit. For example, the scaling problem is performed on one screen with the algorithm of stage 1 202, and the algorithm of stage 2 224 is run on another screen with a different resolution than the screen on which the algorithm of stage 1 202 was run. If executed, it can occur. A grid pattern (eg, grid 400) is useful for applying uniform measurements across multiple screens. In some embodiments, the screen size is predefined, so the set of blocks in the grid can have a predefined amount or dimension. Alternatively, instead of a grid pattern, pixel xy coordinates may be used based on screen resolution and element type. The present disclosure is not limited to only a grid pattern or pixel xy coordinates, and any suitable parameterization for identifying locations within an image may be used.

  [0039] At operation 212, the processing device 114 identifies the text in the initial base screenshot 300. Also at operation 212, the processing device 114 deletes the text from the base screenshot 300 to generate a base image. As described in more detail below, FIG. 5 shows a base screenshot without text 500, ie, a base screenshot with text deleted. For example, the processing device 114 finds text data in the image by applying OCR and ICR techniques and converts the text color to a background color. For example, in the base screenshot 300, the text data “water boiler” has a black text color that covers a different background color (eg, red), and the generation of the base image is the text data “water boiler” is red Including having a color. In some embodiments, OCR and / or ICR techniques may be applied to the base screenshot to find text data.

  [0040] In operation 214, the processing device 114 stores the text data and text location information corresponding to the initial base screenshot 300. The time to capture the screenshot can be used as an identifier for the screenshot, so the time to capture the screenshot can be linked to the text data and text location of the screenshot as a way to indicate the response to the screenshot. Please keep in mind. For example, the processing device 114 determines the location of each text data in the base screenshot and stores the location in the database and corresponding to the text data. For example, the text data in base screenshot 300 may include a string that forms the term “temperature transmitter” over columns 23-29 in the fifth row of the grid. When the box is identified by the {row, column} format, the text data “Temperature Transmitter” has the boxes [5, 23], [5, 24], [5, 25], [5, 26], [5]. , 27] and [5, 28]. Table 1 provides an example of storing text location information corresponding to text data in a database.

  [0041] In operation 216, the processing device 114 assigns identification information to each region of the base screenshot. One or more regions may include smaller regions inside their closed boundaries. That is, the processing device 114 finds each area and each sub-area in the base screenshot. To find a region or subregion, the processing device 114 finds a closed region that is not the same as the background image (indicated by region ID number 0 in FIG. 6). To find a sub-region, the processing device 114 finds a closed region (indicated by region ID number 9.1 in FIG. 6) within another closed region (indicated by region ID number 9 in FIG. 6). As described in more detail below, FIG. 6 shows the regions and subregions of the textless base screenshot 500 of FIG. The processing device 114 assigns an area identification number to each area and lower area. Processing device 114 may assign an identification number to the lower region using a tree structure, such as identifying region 9 as a parent that includes lower region 9.1 as its child.

  [0042] In operation 218, the processing device 114 normalizes the non-uniform color regions of the base screenshot. That is, the processing device 114 applies an equalization method to the region to determine a uniform color for each region that includes two or more colors. For example, by processing the non-text base screenshot 500, the processing device 114 (in the direction from left to right) regions 1-4 have a gradient color that decays from white to black, and region 9.1. Is determined to have a gradient color that decays from black to white. Accordingly, the processing device 114 applies an equalization method to regions 1-4 and subregion 9.1, which results in a determination that the light gray is a uniform color for the multi-color region before these. As described in more detail below, FIG. 7A shows a color-normalized no-text base screenshot.

  [0043] Also in operation 218, the processing device 114 assigns a color to each region. In embodiments where each region is normalized to a uniform color, the processing device 114 assigns a single color, such as an RGB color format, to each region and subregion. Table 2 gives an example of storing region identification numbers corresponding to region colors in a database.

  [0044] In operation 220, the processing device 114 determines the location of each region in the base screenshot and stores the location in the database and corresponding to the region identification number. As described in more detail below, FIG. 7B shows a color normalized text-free base screenshot divided according to the grid 400 of FIG. For example, region 1 covers rows 4-6 of column 8 in the base screenshot. Region 1 corresponds to boxes [4,8], [5,8], and [6,8] when the boxes are identified by the {row, column} format. Table 2 provides an example of storing region identification numbers corresponding to region locations in a database. The block size of the grid pattern can be determined by the screen resolution and the minimum distance between elements and regions in the console station screenshot.

  [0045] The method 200 proceeds from operation 220 to operation 222. In operation 222, the processing device 114 stores the region ID, region color information, region location information, and base image in a database. Method 200 is not limited to storing information in a database as a batch of information, but individual information can also be stored in the database. In some embodiments, method 200 proceeds from operation 216 to operation 222 to store the region ID in the database, and method 200 proceeds to operation 222 after operation 218 to store the base image in the database. Return. Once the base image, text data, and region data are stored in the database, method 200 proceeds from operation 222 to stage 2204. The base image, text data, and region data stored in the database during stage 1202 will be used in a subsequent stage (ie, data reconstruction stage 206) to reconstruct the image. In some embodiments, stage 1202 may consider more parameters from the base image along with text, region, and color information for additional accuracy and performance.

  [0046] Stage 2 204 includes acts 224-236. Method 200 includes repeating step 2 204 periodically, ie, at a frequency of interval T. The interval T is a configurable value based on user selection or user requirements. Stage 2 204 is where the processing device 114 processes the initial base screenshot 300 in stage 1 to identify and store text data and region data, such as Table 1 and Table 2, and in stage 2 204 the process Similar to stage 1202, in that device 114 processes additional base screenshot 300 to identify text data and region data and store them in Table 1 and Table 2, etc. In some embodiments, stage 2 204 is where processing device 114 processes initial base screenshot 300 in stage 1 202 to generate and save base image 700, while processing device 114 is stage 2. At 204, it may differ from stage 1202 in that an additional base screenshot 300 may not be saved. Some embodiments of stage 2 204 may include the act of saving an additional base screenshot 300 in the database in addition to the corresponding text and region data for each interval T, such as Note that embodiments may consume more memory than other embodiments that store corresponding text data and region data for each interval T without storing the additional base screenshot 300 itself. I want to be. In some embodiments, stage 2 204 may consider more parameters from the base image along with text, region, and color information for additional accuracy and performance.

  [0047] At operation 224, the processing device 114 captures additional base screenshots. This subsequent image of the operator console display screen view is captured by the FAMS application 120 after the elapse of interval T starting at the completion of capturing the previous image or screen shot. In some situations, the interval T may elapse without changes in the text data shown on the display screen in the operator console 110, and in such situations, the additional base screenshot may be the same as the previous base screenshot. It may look like the equivalent. As a specific example, the additional base screen shot may appear to be equivalent to the initial base screen shot 300 of FIG. In other situations, changes in the text data or color data shown on the display screen in operator console 110 may occur during interval T, in which case the additional base screenshot may be the previous base screenshot. Can look different.

  [0048] In operation 226, the processing device 114 identifies the text in the additional base screenshot. For example, the processing device 114 finds text data in the image by applying OCR and ICR techniques.

  [0049] In operation 228, the processing device 114 stores text data and text location information corresponding to the additional base screenshot. For example, the processing device 114 can divide the additional base screenshot into a grid and determine text location information in a manner similar to operation 210.

  [0050] At operation 230, the processing device 114 identifies one or more regions in the additional base screenshot. That is, the processing device 114 finds each region and each subregion in the additional base screenshot.

  [0051] At operation 232, the processing device 114 normalizes the non-uniform color regions of the additional base screenshot in the same manner as in operation 218. In operation 234, the processing device 114 assigns a region identification number to each region and each subregion identified or otherwise found in operation 230. In some embodiments, operation 234 also causes processing device 114 to determine the location of each region in the additional base screenshot and store that location in the database and corresponding to the region identification number. Including. In operation 236, the processing device 114 assigns a color to each region and subregion of the additional base screenshot, as in operation 218.

  [0052] The method 200 proceeds from operation 236 to operation 222. Once the text data and region data corresponding to the additional base screenshot are stored in the database, the method 200 proceeds from operation 222 to operation 224 to repeat step 2204. Note that there is a difference between stage 1 202 and stage 2 204 in operation 222, that is, it is not necessary to store the base image as part of operation 222 in stage 2 204. However, more images can be stored in stage 2 204 for additional accuracy and performance. When the processing device 114 receives input indicating a user selection to replay some of the archived periodic screenshots, the method proceeds from operation 222 to the data reconstruction stage 206.

  [0053] The data reconstruction stage 206 includes an action 238, an action in stage 3 240, an action in stage 4 250, and an action in stage 5 252. In operation 238, the processing device 114 retrieves the base image from the storage. That is, the processing device 114 accesses the base image generated in stage 1202 and stored in operation 222.

  [0054] At stage 3 240, the method 200 includes iteratively reconstructing a new image for each time interval (T). More particularly, the method of forming an image from the stored data at stage 3 240 is implemented by the processing device 114 and retrieves the stored color data at operation 242 and the retrieved color at operation 244. The data is applied to the base image, the stored text data is retrieved at operation 246, and the retrieved text data is superimposed on the colored base image at operation 248. In an embodiment where stage 1 202 and / or stage 2 204 considers additional parameters along with text, region, and color information for additional accuracy and performance in the console station screenshot or base image, in stage 3 240 Note that there are additional respective actions.

  [0055] As a non-limiting example of reconstructing a new image for the time interval during which the initial base screenshot 300 of FIG. 3 was captured, the processing device 114 may store the color data stored in Table 2 (Operation 242), and applies the retrieved color data to the corresponding region of the base image according to the region location information stored in Table 2 (operation 244). The base image 700 in FIG. 7B shows that the grid 400 is used to locate where the normalized colors in Table 2 apply to the no-text base image 700. Further, the processing device 114 retrieves the text data stored in Table 1 (operation 246) and superimposes the retrieved text data on the colored base image (operation 248). 8A and 8B provide examples of reconstructed images 800 and 801 for the time interval during which the initial base screenshot 300 was captured. The processing device 114 uses the grid 400 to locate where each text data from Table 1 of the initial base screenshot 300 overlaps with the colored base image 700 according to the text location information stored in Table 1. . When a new image for each of the time intervals (T) corresponding to the user selection to replay some of the archived periodic screenshots is reconstructed, the method 200 proceeds to step 4250.

  [0056] At stage 4 250, the processing device 114 identifies images and data that exhibit a spot color. That is, the processing device 114 identifies reconstructed base images and data that have unique behavior. The processing device 114 can identify specific images and / or specific data by visually highlighting them. Examples of specific behavior include images with devices that have suddenly changed color (eg, from one frame to the next, or within a limited number of consecutive frames), sudden pressure and / or volume ( There is an image with a PV) drop, an image with a sudden increase in pressure and / or volume, or an image with a sudden alarm (s). In some embodiments, the user selection can set a limited number of consecutive frames within which a sudden change in color, PV, or alarm status occurs as an indicator of the specific behavior. In some embodiments, the processing device 114 may access a predetermined limited number of consecutive frames within which a sudden change in color, PV, or alarm status occurs as a characteristic behavior indicator. it can.

  [0057] At stage 5252, the processing device 114 represents the reconstructed image and stored data. More particularly, the processing device 114 provides a display screen in the operator console 110 that includes the stored data and reconstructed images formed during the previous phase (see FIGS. 9A and 9B). Implement the root cause analysis tool user interface (UI) (shown).

  [0058] FIGS. 2A and 2B illustrate one exemplary method 200 for performing post-mortem analysis of a tripped field device in the process industry using OCR and ICR techniques, Changes can be made to FIGS. 2A and 2B. For example, the various steps in the figures can be overlapped, performed in parallel, or performed any number of times. That is, some of these operations may be performed more than once or in a different order, or some additional unspecified operations may also be performed for best performance and accuracy. As another example, in operation 210, the base image may be replaced with a grid pattern (shown in FIG. 4) where the xy coordinate values of each region and text (shown in FIG. 10) pixels. Or it will be split so that it can be used as an addition. When applying a coordinate system, the location of each pixel in the screenshot may be defined by an x value and a y value, each corresponding to a relative location from the origin of the coordinate system.

  [0059] FIG. 3 illustrates an exemplary base screenshot 300 of an operator console 110 display screen that provides a view of a selected critical device of a process unit in accordance with the present disclosure. The base screenshot 300 shows the background, the critical process unit containing the selected critical device, the label of the critical device, the process flow connector arrow, the process variable value in the block associated with the critical device, and the process variable value. Use to draw a critical device and a controller to control the process flow. The controller can be a component within the process unit, or the controller can be a preprogrammed processing device, and for simplicity, FIG. 3 shows whether the controller is a selected critical device of the process unit. It is explained as follows.

  [0060] In the illustrated example, the background 305 has a background color, such as dark gray. Selected critical devices of the process unit include valve 310, boiler 315, temperature transmitter 320, and controller 325. The valve 310 may have a green color, for example, the boiler 315 may have a red color, and the temperature transmitter 320 may have a red color. The controller 325 is drawn as three similarly sized rectangular boxes and a longer rectangular box, each of which has a gradient color that decays from white to black (in the direction from left to right). The temperature transmitter 320 is depicted as a crescent, a circle above a vertically elongated rectangle, a vertically elongated rectangle, each of which has a red color. The temperature transmitter 320 further includes a rectangular portion 330 within the circle, the rectangular portion 330 being a different color from its red surroundings, with a slope that attenuates from black to white (in the direction from left to right). Have a color. The text, ie the critical device label and the process variable value, is black. Furthermore, the process flow connector arrow has the same color as the text, ie black. The process variable value blocks 335a-335b have a color that is the same as the background color, i.e. dark gray. In some embodiments, the process industry console station 110 uses images recommended by the International Society of Automation (ISA), but this is not required and non-ISA images may be used.

  [0061] In the process unit, the valve 310 receives the water inlet flow and provides the outlet flow to the water boiler 315, such as by pumping the outlet flow to the boiler using a water pump. The process variable value “31%” depicted in the process variable value block 335a indicates the percentage of the valve opened. Thus, the valve 310 receives or outputs 31% of its throughput capacity. Boiler 315 boiles the fluid received from valve 310 and provides output flow. The process variable value “21 ° C.” drawn in the process variable value block 335 b indicates the current temperature of the fluid in the boiler 315. A temperature sensor may be associated with the boiler 315 to measure the temperature of the fluid in the boiler 315 and provide a temperature measurement to the temperature transmitter 320. The temperature transmitter 320 may use the temperature sensor to obtain the temperature measurement as a process variable value “21 ° C.”, provide the temperature measurement to the controller, and send the process variable value to the receiver of another device. it can. For example, the controller 325 controls the position of the valve 310 based on the temperature measurement provided by the temperature transmitter 320.

  [0062] Although FIG. 3 shows one exemplary base screenshot 300, various changes may be made to FIG. For example, different process units may be depicted, or process units may include more, fewer, or different field devices.

  [0063] FIG. 4 shows the base screenshot 300 of FIG. 3 divided into a grid 400 in accordance with the present disclosure. In the illustrated example, the grid 400 includes 18 rows and 30 columns. Grid 400 includes a set of blocks based on image size so that the blocks do not overlap. That is, each part of the base screen shot 300 is covered by one block of the grid 400. In some embodiments, each portion of the base screenshot 300 is covered by an entire block of the grid 400, and thus no portion of the base screenshot is covered by a partial, smaller block than the entire block. . Each block in grid 400 may be equal in size to each other block in grid 400.

  [0064] The embodiment of the grid 400 shown in FIG. 4 is for illustration only. Other embodiments may be used without departing from the scope of this disclosure. For example, other embodiments can include a different number of rows or columns in the grid.

  [0065] FIG. 5 illustrates a textless base screenshot 500 in accordance with the present disclosure. That is, FIG. 5 shows the base screenshot of FIG. 3 with the text data deleted.

  [0066] The text data of the initial base screenshot 300 deleted from the no text base screenshot 500 includes critical device labels, ie, “controller”, “temperature transmitter”, “water boiler”, and “valve”. . The text data of the initial base screenshot 300 deleted from the no text base screenshot 500 further includes process variable values “21 ° C.” and “31%”.

  [0067] Note that the OCR and ICR techniques can distinguish the boundaries of the process variable value blocks 335a-335b from the text data that each contains. Accordingly, the no text base screenshot 500 includes process variable value blocks 335a-335b.

  [0068] FIG. 6 illustrates regions and subregions of the textless base screenshot 500 of FIG. 5, in accordance with this disclosure. That is, the region ID shown in FIG. 6 is for illustration only and is not part of the image of the base screen shot 500 without text.

  [0069] In the illustrated example, the no text base screenshot 500 includes regions 0-11 and a subregion 9.1. Region 0 is the background 305. Region 1 is the longer rectangular box of controller 325. Regions 2, 3, and 4 are three similarly sized rectangular boxes of the controller 325. Region 5 is a boiler 315. Region 6 is a button vertical section type portion of the valve 310, and regions 7 and 8 are triangular portions of the valve 310. The region 9 is a circular portion of the temperature transmitter 320, and the region 10 is a rectangular portion elongated in the vertical direction of the temperature transmitter 320. The lower region 9.1 is a rectangular portion 330 in the circle of the temperature transmitter 320. Area 11 is a process variable value block 335b, and area 12 is a process variable value block 335a.

  [0070] Although FIG. 6 shows one exemplary identification of the region and subregion of the base screenshot without text, various changes may be made to FIG. For example, the regions may be identified in a different order, or may be identified in alphabetical order or alphanumeric order.

  [0071] FIGS. 7A and 7B illustrate a base image 700 according to the present disclosure. FIG. 7A shows that the base image 700 is a color normalized result of applying color equalization to the textless base screenshot 500 of FIG. FIG. 7B shows the base image 700 of FIG. 7A divided according to the grid 400 of FIG.

  [0072] As a non-limiting example, regions 0, 11, and 12 can be assigned a dark gray color, regions 1-4 and subregion 9.1 can be assigned a light gray color, and regions 5 and 9-10. May be assigned a red color and regions 6-8 may be assigned a green color. This color convention is only used for illustration. In other cases, there can be any color to represent the health of each element.

  [0073] Although FIGS. 7A and 7B show one exemplary base image 700, various changes may be made to FIGS. 7A and 7B. For example, regions 1-4 and subregion 9.1 can be normalized to different shades or colors.

  [0074] FIGS. 8A and 8B show examples of reconstructed images 800 and 801 for the time interval during which the initial screenshot 300 of FIG. 3 was captured. The embodiment of reconstructed images 800, 801 shown in FIGS. 8A and 8B is for illustration only. Other embodiments may be used without departing from the scope of this disclosure.

  [0075] In situations where the interval T elapses without any change in the text data shown on the display screen in the operator console 110, the reconstructed image 800 is like a color normalized version of the previous base screenshot. Can be seen. As a specific example, the reconstructed image 800 of FIG. 8A may look like a color normalized version of the initial base screenshot 300 of FIG. In other situations where a change in text or color data shown on the display screen in operator console 110 occurs during interval T, the reconstructed image is a color normalized version of the previous base screenshot. Can look different.

  [0076] FIG. 8B shows that when color gradient information is stored as part of operation 222, the reconstructed image 801 can have regions with color gradients. If any region has more than one gradient color, and if there is an image reconstruction requirement for a perfect match with the screenshot 300 of the console station 110, each possible region image is extracted and (local Each link to the stored region image will be given in Table 2. Similarly, the xy coordinates of the pixels for each region and each text may be stored, and the reconstructed image 801 will be configured to exactly match the original console station screenshot.

  [0077] FIGS. 9A and 9B illustrate a root cause analysis tool user interface (UI) of a display screen in an operator console 110 according to the present disclosure. The FAMS application 120 includes an RCA tool UI. FIG. 9A shows an image view 900 of the RCA tool UI, and FIG. 9B shows a table view 901 of the RCA tool UI. The RCA tool UI shows the stored data and the reconstructed image formed during stages 1-4202, 204, 240, 250. The processing device 114 may implement the RCA tool UI image view 900 and table view 901 by controlling or communicating with a display screen in the operator console 110.

  [0078] As shown in FIG. 9A, the image view 900 of the RCA tool UI includes an image display box 905, a set of thumbnails 910, 915, 920 for each category of images, and a selected category of images. Timeline 925 for image and image thumbnails 930a-930g from the selected category of images. An image display box 905 displays the currently selected image in the full size format. For example, the image display box 905 can indicate the reconstruction of the initial base screenshot. As another example, in response to receiving a user selection of one of the image categories corresponding to the set of thumbnails 910, 915, 920, the image display box 905 displays images from the selected set of thumbnails. Can be shown. As another example, in response to receiving a user selection of one of the image thumbnails 930a-930g, the image display box 905 can indicate the full size format of the selected image thumbnail.

  [0079] In the illustrated example, there are image categories, the "all images" category corresponds to the set of thumbnails 910, the "specific image" category corresponds to the set of thumbnails 915, and the "user selected image" The category corresponds to a set 920 of thumbnails. All image sets 910 of thumbnails include all of the images formed using the method 200 for performing post-mortem analysis of a tripped field device in the process industry using OCR and ICR techniques.

  [0080] The thumbnail specific image set 915 assists the user in identifying the root cause of field device tripping occurrences in the process unit. The processing device 114 performs the operation of stage 4 250 to show the operator one or more images that have exceeded the operational limits of the field device. The thumbnail specific image set 915 includes images exhibiting the features identified in the operations within stage 4250. That is, the thumbnail set 915 includes a subset of all thumbnail image sets 910. The thumbnail specific image set 915 may be a null set when none of the images exhibit the process unit specific behavior.

  [0081] A user-selected image set 920 of thumbnails includes images selected by user selection. For example, the user has a selection right to select the image to form a new category, i.e. a category called "user selected image". The user can add any image from the “all images” category or the “specific image” category to the user selected image set 920 of thumbnails to add the dragged / dropped image to the user selected image category. Can be dragged and dropped. The user-selected image set 920 of thumbnails can be a null set when none of the images are selected by the operator.

  [0082] The timeline 925 for the selected category of images represents the time period during which the selected category of images was captured. For example, when the “all images” category is selected, the timeline 925 is displayed from a start time (eg, indicated by reference number 960a in FIG. 9B) to a stop time (eg, indicated by reference number 960b in FIG. 9B). Represents the time period until. The start time may be when the initial base screenshot is captured. Examples of stop times include, but are not limited to, when the most recent additional base screenshot was captured, at a user-selected time, or a selected number of intervals T after the initial base screenshot was captured. There is. The timeline 925 further includes a timeline bar 928 that visually represents a particular time point or a particular subset of times between the start time and the stop time. For example, the timeline bar 928 may represent a subset of times during which image captures corresponding to the image thumbnails 930a-930g occurred.

  [0083] In the illustrated example, the image thumbnails 930a-930g are labeled "image thumbnails in the timeline". That is, image thumbnails 930a-930g from the selected category of images appear in an order according to the timeline.

  [0084] Although FIG. 9A shows one exemplary image view 900 of the RCA tool UI, various changes may be made to FIG. 9A. For example, each component in FIG. 9A can have any other size, shape, and dimensions.

  [0085] As shown in FIG. 9B, the table view 901 of the RCA tool UI includes a table 955 of field device data during a particular time period and various filters 960a for filtering the field device data. -960d and thumbnail images 965a-965d representing tables for other station views. Table 955 includes a column 970 of times when data was recorded. For example, the interval T can be 1 second, so each row can contain field device data recorded for each interval T. Table 955 further includes a column 975 for each field device in a particular process unit. A particular process unit may be any number of field devices (Dev-1-PV, Dev-2-PV, ... Dev-n-PV), such as pressure valves or other devices related to pressure and / or volume. Can be included. The cells in the table 955 can highlight highlights visually, such as by displaying differently colored cells or differently highlighted fonts. A spot color can be a noticeable change in a value in field device data. That is, the highlighted data 980a-980b assists the user in identifying the root cause of field device tripping in the process unit. The processing device 114 performs the operation of stage 4 250 to show the operator one or more images that have exceeded the operational limits of the field device.

  [0086] As a specific non-limiting example, the field device DEV-3-PV is its steep, ie, from a value of 20 at time 10:01:04 to a value of 0 at time 10:01:05. It exhibits a unique behavior by reducing its value. A 20 unit change or reduction in value may be a noticeable change (eg, a change in threshold amount), depending on the RCA tool user interface (UI) settings. As another example, the field device DEV-5-PV is characterized by its abrupt, ie increasing value from a value of 20 at time 10:01:04 to a value of 155 at time 10:01:05. It exhibits the following behavior. A 135 unit change or increase in value may be a noticeable change depending on the RCA tool user interface (UI) settings. In these examples, the 0 and 155 values for field device data may be outside the normal operating range of the device or other operating limits, and thus the color of the cell containing the non-unique value (eg, lavender ) Is highlighted in a color different from (for example, red). That is, from time 10:01:05 to time 10:01:09, field devices DEV-3-PV and DEV-5-PV have highlighted field device data.

  [0087] In the illustrated example, the table view 901 of the RCA tool UI includes four filters, but any suitable number of filters may be applied to the table 955. Examples of filters include a text box for start time filter 960a, a text box for stop time filter 960b, a list box for device list filter 960c, or other suitable selection for user defined filter 960d. Adjusted based on user selection, such as using the method. The range of the time column 970 is determined by the time 10:01:01 as the setting of the start time filter 960a and the time 10:01:10 as the setting of the stop time filter 960b.

  [0088] In the illustrated example, the thumbnail images 965a-965d represent a table for four other station views, but any suitable number of thumbnail images may be displayed in the table view 901 of the RCA tool UI. . As explained above, the FAMS application 120 provides a tool for selecting available views of various process units running on various operator consoles 110, and thus the thumbnail image 965a is one operator. Each of the other thumbnail images 965b to 965d corresponds to the second to fourth process units that run on different operator consoles 110, respectively. can do.

  [0089] Although FIG. 9B shows one exemplary table view 901 of the RCA tool UI, various changes may be made to FIG. 9B. For example, each component in FIG. 9B can have any other size, shape, and dimensions.

  [0090] FIG. 10 illustrates a coordinate system 1000 applied to the base screenshot 300 of FIG. 3, in accordance with the present disclosure. For further accuracy and performance, the processing device 114 may include a coordinate system 1000 on any initial or subsequent screenshot for use in parameterizing the location of each text data and each region in the base screenshot. Can be applied. In coordinate system 1000, the location of each pixel in the screenshot may be defined by an x value 1005 and a y value 1010, each corresponding to a relative location from the origin 1015 of the coordinate system. As an example, the origin 1015 can be the upper left corner of the base screenshot 300, so the pixel at the origin 1015 has a zero y value and a zero x value.

  [0091] As an example, the processing device 114 may determine that the process variable value block 335b, ie, the text data in the region 12, has a left boundary 1020 and an upper boundary 1025 that form vertices at the pixel 1030. . The processing device 114 may determine that the vertex pixel 1030 or the left boundary 1020 is arranged horizontally or rightward by an x value of 1005 pixels from the origin 1015. Processing device 114 may determine that vertex pixel 1030 or upper boundary 1025 is positioned vertically or downward by 1010 pixels of y value from origin 1015. The processing device 114 can apply a similar process to determine other boundaries of the region or other text data locations. For example, the processing device 114 may determine that the process variable value block 335 b, ie, the text data in the region 11, has a left boundary 1035 and an upper boundary 1040 that form a vertex at the pixel 1045.

  [0092] As shown in FIG. 10, the x and y coordinates of a pixel may be used for further accuracy and performance. In some embodiments, the xy coordinate values of the rectangular pixels that cover the elements (ie, text, regions, etc.) in the base screenshot 300 are also used for better accuracy than the grid 400 of FIG. Can be done.

  [0093] In some embodiments, the various functions described above are implemented or supported by a computer program formed from computer-readable program code and implemented on a computer-readable medium. The phrase “computer readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer readable medium” is accessed by a computer, such as read only memory (ROM), random access memory (RAM), hard disk drive, compact disk (CD), digital video disk (DVD), or other type of memory. Any type of media that can be played. “Non-transitory” computer-readable media excludes wired, wireless, optical, or other communication links that transport transient electrical or other signals. Non-transitory computer readable media include media in which data can be permanently stored and media in which data can be stored and later overwritten, such as rewritable optical discs or erasable memory devices.

  [0094] It may be advantageous to provide definitions of some words and phrases used throughout this patent document. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or (source code, object code, or Refers to those portions adapted for implementation in suitable computer code (including executable code). The terms “include” and “comprise” and derivatives thereof are meant to include, but not be limited to. The term “or” is inclusive and / or means and / or. The phrase “associated with” and its derivatives are included, included within, interconnected with, included, included within. To or to, to or to, to be able to communicate with, to cooperate with, to interleave, juxtapose to, to be close to, to or It may mean to be associated with, having, having the property of, having a relation to or with. The phrase “at least one of” when used with an enumeration of items means that one or more different combinations of the listed items can be used, and that only one item in the enumeration It means that it can be needed. For example, “at least one of A, B, and C” means any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C Is also included.

  [0095] Although this disclosure describes several embodiments and generally related methods, modifications and substitutions to these embodiments and methods will be apparent to those skilled in the art. Accordingly, the above description of example embodiments does not define or constrain this disclosure. Other changes, substitutions, and modifications are possible without departing from the spirit and scope of the present disclosure as defined by the following claims.

Claims (15)

Capturing (208) at least one screenshot of a display screen including an initial screenshot (300);
Deleting text from the initial screenshot to generate a base image (500, 700) (212);
Identifying the background (region 0) of the initial screenshot as a closed region (216);
For each of the at least one screenshot,
Storing (222) the time (970) to capture the screenshot;
Identifying (212, 226) text, text color, and text location in the screenshot;
Identifying each closed region (regions 1-12) in the screenshot that is different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot. (216, 230),
Storing (222) the region color and the region location for each identified closed region;
Storing (214, 228) the text color and the text location of the identified text. For each new image,
Retrieving the base image (238);
Corresponding to one of the at least one captured screenshot and its stored time to capture,
Retrieving (242) the region color and region location for each identified region, and the text color and text location of the identified text;
Applying the searched area color to each area of the base image at the searched area location (244);
Overlaying the retrieved base image with the text in the retrieved text color (248) at the retrieved text location as at least one reconstruction of the at least one captured screenshot. The method of claim 1, further comprising generating (238, 240) two new images (800, 801). Identifying (250) a new image exhibiting a spot color (980a, 980b), wherein the spot color is a change in field device data by at least a threshold amount or field device data operating outside operating limits Identifying (250) comprising at least one of:
Generating a user interface display screen (900, 901) that highlights the spot color (252). Capturing the at least one screenshot of the display screen;
Periodically capturing additional screen shots according to a specified time interval (224);
The method of claim 1 comprising: Dividing the screenshot into grids (210);
Determining the text location according to the grid;
The method of claim 1, further comprising determining the region location according to the grid. Dividing the screenshot into grids;
6. The method of claim 5, comprising one of applying a coordinate system (1000) to the screen shot, or dividing the screen shot into a set of blocks (400) organized in rows and columns. The method described. A memory (116);
At least one processor (114) coupled to the memory, the at least one processor comprising:
Capturing at least one screenshot of the display screen including an initial screenshot (300);
Deleting text from the initial screenshot to generate a base image (500, 700);
Identifying the background (region 0) of the initial screenshot as a closed region;
For each of the at least one screenshot,
Storing the time to capture the screenshot (970) in the memory;
Identifying the text, text color and text location in the screenshot;
Identifying each closed region (regions 1-12) in the screenshot that is different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot When,
Storing the region color and the region location for each identified closed region in the memory;
An apparatus configured to: store the text color and the text location of the identified text in the memory. For each new image, the processor
Retrieving the base image;
Corresponding to one of the at least one captured screenshot and its stored time to capture,
Retrieving the region color and region location for each identified region, and the text color and text location of the identified text;
Applying the searched area color to each area of the base image at the searched area location;
At the retrieved text location, at least one new image as a reconstruction of the at least one captured screenshot by overlaying the retrieved base image with the text in the retrieved text color. The apparatus of claim 7, further configured to generate (800, 801). The processor is
Identifying a new image exhibiting a spot color (980a, 980b), wherein the spot color is a change in field device data by at least a threshold amount, or at least one of field device data operating outside operating limits. Including, identifying,
8. The apparatus of claim 7, further configured to generate a user interface display screen (900, 901) that highlights the spot color. The processor is
The apparatus of claim 7, further configured to capture the at least one screen shot of the display screen by periodically capturing additional screen shots according to a specified time interval. A non-transitory computer readable medium for implementing a computer program, wherein when the computer program is executed by a processing circuit, the processing circuit
Capturing (208) at least one screenshot of a display screen including an initial screenshot (300);
Deleting text from the initial screenshot to generate a base image (212);
Identifying the background (region 0) of the initial screenshot as a closed region (216);
For each of the at least one screenshot,
Storing in memory a time to capture the screenshot (970) (222);
Identifying (212, 226) the text, text color, and text location in the screenshot;
Identifying each closed region (regions 1-12) in the screenshot that is different from the background of the initial screenshot, and the region color and region location for each identified closed region in the screenshot (216, 230),
Storing the region color and the region location for each identified closed region (222);
A non-transitory computer readable medium comprising computer readable program code for causing said text color and said text location of said identified text to be stored (214, 228). When the computer program is executed by the processing circuit, the processing circuit
Retrieving the base image (238);
Corresponding to one of the at least one captured screenshot and its stored time to capture,
Retrieving (242) the region color and region location for each identified region, and the text color and text location of the identified text;
Applying the retrieved region color to each region of the base image at the retrieved region location (244);
At least one reconstruction of the at least one captured screenshot by superimposing (248) the retrieved base image with the text in the retrieved text color at the retrieved text location. 12. The non-transitory computer readable medium of claim 11, further comprising computer readable program code that causes generating (238, 240) two new images (800, 801). When the computer program is executed by the processing circuit, the processing circuit
Identifying (250) a new image exhibiting a spot color (980a, 980b), wherein the spot color is a change in field device data by at least a threshold amount or field device data operating outside operating limits Identifying (250) including at least one of:
The non-transitory computer readable medium of claim 11, further comprising computer readable program code for generating (252) a user interface display screen (900, 901) that highlights the feature. When the computer program is executed by the processing circuit, the processing circuit
The computer-readable program code for causing the at least one screenshot of the display screen to be captured by periodically capturing (224) additional screen shots according to a specified time interval. A non-transitory computer readable medium according to claim 1. When the computer program is executed by the processing circuit, the processing circuit
Identifying each closed region within the identified region as a subregion (region 9.1);
The non-transitory computer readable medium of claim 11, further comprising computer readable program code for causing a region identification to be assigned to each identified region and subregion using a tree structure.

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